19 citations · 57 across the 18 of their papers we have counts for
3 papers · 1 filter
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits
Arun Verma, Zhongxiang Dai, Yao Shu +1
We study a novel variant of the parameterized bandits problem in which the learner can observe additional auxiliary feedback that is correlated with the observed reward. The auxili…
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai +5
Large language models (LLMs) have shown remarkable instruction-following capabilities and achieved impressive performances in various applications. However, the performances of LLM…
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients
Yao Shu, Xiaoqiang Lin, Zhongxiang Dai +1
Federated optimization, an emerging paradigm which finds wide real-world applications such as federated learning, enables multiple clients (e.g., edge devices) to collaboratively o…